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Stochastic simulation of reaction-diffusion systems presents great challenges for spatiotemporal biological models. A straightforward extension of Gillespie's stochastic simulation algorithm (SSA) for spatially inhomogeneous systems leads to the Inhomogeneous Stochastic Simulation Algorithm (ISSA). However, the ISSA can be prohibitively expensive in computation, especially when the mesh size is too...
Many protein regulatory models contain chemical species best represented as having multiple states. Such models stem from the potential for multiple levels of phosphorylation or from the formation of multiprotein complexes. We seek to support such models by augmenting an existing modeling and simulation system. Interactions between multistate species can lead to a combinatorial explosion in the potential...
This paper reports a web-based Problem Solving Environment (PSE) system to consider models for human choice behavior. This system collects behavioral data which human subjects chose facilities. Using this system, they choose a facility according to the information such as congestion level for the facility they chose in the previous turn. We examine several models to simulate behaviors of human choice...
In order to scientifically and objectively evaluate resource-based cities innovation capacity, the entropy is adopted to select the evaluation indexes, whose weights are then determined by analytic network process (ANP) model. This method is applied to evaluate Daqing's innovative capacity since 1998 to 2005. The result shows that the city's innovative capacity improved itself annually. The method...
Insulin secreted by pancreatic islet β-cells is the principal regulating hormone of glucose metabolism. Disruption of insulin secretion may cause glucose to accumulate in the blood, and result in diabetes mellitus. Although deterministic models of the insulin secretion pathway are available, the stochastic aspect of the biological pathway has not been explored. As a first step in this direction, we...
Gillespie's stochastic simulation algorithm (SSA) has been a conventional method for stochastic modeling and simulation of biochemical systems. However, as a population-based algorithm it faces the challenge of combinatorial complexity in many biochemical models where species may present with multiple states. To solve this problem, the rules-based modeling was proposed by Hlavacek's group and the...
We present a time-varying fractional autoregressive integrated moving average model and the methodology to fit this model to a non-stationary time series with local stationarity. Our experiments illustrate that the proposed model is able to capture the non-stationarity of traffic with time-varying parameters. An application to Internet traffic data is presented.
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